Antiviral Effectiveness, Clinical Outcomes, and Artificial Intelligence Imaging Analysis for Hospitalized COVID-19 Patients Receiving Antivirals.

INTRODUCTION: There is still a lack of clinical evidence comprehensively evaluating the effectiveness of antiviral treatments for COVID-19 hospitalized patients. METHODS: A retrospective cohort study was conducted at Beijing You'An Hospital, focusing on patients treated with nirmatrelvir/ritonavir or azvudine. The study employed a tripartite analysis-viral dynamics, survival curve analysis, and AI-based radiological analysis of pulmonary CT images-aiming to assess the severity of pneumonia. RESULTS: Of 370 patients treated with either nirmatrelvir/ritonavir or azvudine as monotherapy, those in the nirmatrelvir/ritonavir group experienced faster viral clearance than those treated with azvudine (5.4 days vs. 8.4 days, p < 0.001). No significant differences were observed in the survival curves between the two drug groups. AI-based radiological analysis revealed that patients in the nirmatrelvir group had more severe pneumonia conditions (infection ratio is 11.1 vs. 5.35, p = 0.007). Patients with an infection ratio higher than 9.2 had nearly three times the mortality rate compared to those with an infection ratio lower than 9.2. CONCLUSIONS: Our study suggests that in real-world studies regarding hospitalized patients with COVID-19 pneumonia, the antiviral effect of nirmatrelvir/ritonavir is significantly superior to azvudine, but the choice of antiviral agents is not necessarily linked to clinical outcomes; the severity of pneumonia at admission is the most important factor to determine prognosis. Additionally, our findings indicate that pulmonary AI imaging analysis can be a powerful tool for predicting patient prognosis and guiding clinical decision-making.

Computation of random time-shift distributions for stochastic population models.

Even in large systems, the effect of noise arising from when populations are initially small can persist to be measurable on the macroscale. A deterministic approximation to a stochastic model will fail to capture this effect, but it can be accurately approximated by including an additional random time-shift to the initial conditions. We present a efficient numerical method to compute this time-shift distribution for a large class of stochastic models. The method relies on differentiation of certain functional equations, which we show can be effectively automated by deriving rules for different types of model rates that arise commonly when mass-action mixing is assumed. Explicit computation of the time-shift distribution can be used to build a practical tool for the efficient generation of macroscopic trajectories of stochastic population models, without the need for costly stochastic simulations. Full code is provided to implement the calculations and we demonstrate the method on an epidemic model and a model of within-host viral dynamics.

Allometric comparison of viral dynamics in the nasal cavity-nasopharyngeal mucus layer of human and rhesus monkey by CFD-HCD approach.

BACKGROUND AND OBJECTIVE: Viral respiratory infections stand as a considerable global health concern, presenting significant risks to the health of both humans and animals. This study aims to conduct a preliminary analysis of the time series of viral load in the nasal cavity-nasopharynx (NC-NP) of the human and rhesus macaque (RM). METHODS: Taking into account the random uniform distribution of virus-laden droplets with a diameter of 10 µm in the mucus layer, this study applies the computational fluid dynamics-host cell dynamics (CFD-HCD) method to 3D-shell NC-NP models of human and RM, analyzing the impact of initial distribution of droplets on the viral dynamics of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), estimating parameters in the HCD model based on experimental data, integrating them into simulations to predict the time series of viral load and cell counts, and being visualized. The reproductive number (R0) are calculated to determine the occurrence of infection. The study also considers cross-parameter combinations and cross-experimental datasets to explore potential correlations between the human and RM. RESULTS: The research findings indicate that the uniform distribution of virus-laden droplets throughout the whole NC-NP models of human and RM is reasonable for simulating and predicting viral dynamics. The visualization results offer dynamic insights into virus infection over a period of 20 days. Studies involving parameter and dataset exchanges between the two species underscore certain similarities in predicting virus infections between the human and RM. CONCLUSIONS: This study lays the groundwork for further exploration into the parallels and distinctions in respiratory virus dynamics between humans and RMs, thus aiding in making more informed decisions in research and experimentation.

Within-Host Viral Growth and Immune Response Rates Predict Foot-and-Mouth Disease Virus Transmission Dynamics for African Buffalo.

AbstractInfectious disease dynamics operate across biological scales: pathogens replicate within hosts but transmit among populations. Functional changes in the pathogen-host interaction thus generate cascading effects across organizational scales. We investigated within-host dynamics and among-host transmission of three strains (SAT-1, -2, -3) of foot-and-mouth disease viruses (FMDVs) in their wildlife host, African buffalo. We combined data on viral dynamics and host immune responses with mathematical models to ask the following questions: How do viral and immune dynamics vary among strains? Which viral and immune parameters determine viral fitness within hosts? And how do within-host dynamics relate to virus transmission? Our data reveal contrasting within-host dynamics among viral strains, with SAT-2 eliciting more rapid and effective immune responses than SAT-1 and SAT-3. Within-host viral fitness was overwhelmingly determined by variation among hosts in immune response activation rates but not by variation among individual hosts in viral growth rate. Our analyses investigating across-scale linkages indicate that viral replication rate in the host correlates with transmission rates among buffalo and that adaptive immune activation rate determines the infectious period. These parameters define the virus's relative basic reproductive number (ℛ0), suggesting that viral invasion potential may be predictable from within-host dynamics.

Differences in HIV-1 reservoir size, landscape characteristics and decay dynamics in acute and chronic treated HIV-1 Clade C infection.

Background: Persisting HIV reservoir viruses in resting CD4 T cells and other cellular subsets are the main barrier to cure efforts. Antiretroviral therapy (ART) intensification by early initiation has been shown to enable post-treatment viral control in some cases but the underlying mechanisms are not fully understood. We hypothesized that ART initiated during the hyperacute phase of infection before peak will affect the size, decay dynamics and landscape characteristics of HIV-1 subtype C viral reservoirs. Methods: We studied 35 women at high risk of infection from Durban, South Africa identified with hyperacute HIV infection by twice weekly testing for plasma HIV-1 RNA. Study participants included 11 who started ART at a median of 456 (297-1203) days post onset of viremia (DPOV), and 24 who started ART at a median of 1 (1-3) DPOV. We used peripheral blood mononuclear cells (PBMC) to measure total HIV-1 DNA by ddPCR and to sequence reservoir viral genomes by full length individual proviral sequencing (FLIP-seq) from onset of detection of HIV up to 1 year post treatment initiation. Results: Whereas ART in hyperacute infection blunted peak viremia compared to untreated individuals (p<0.0001), there was no difference in total HIV-1 DNA measured contemporaneously (p=0.104). There was a steady decline of total HIV DNA in early treated persons over 1 year of ART (p=0.0004), with no significant change observed in the late treated group. Total HIV-1 DNA after one year of treatment was lower in the early treated compared to the late treated group (p=0.02). Generation of 697 single viral genome sequences revealed a difference in the longitudinal proviral genetic landscape over one year between untreated, late treated, and early treated infection: the relative contribution of intact genomes to the total pool of HIV-1 DNA after 1 year was higher in untreated infection (31%) compared to late treated (14%) and early treated infection (0%). Treatment initiated in both late and early infection resulted in a more rapid decay of intact (13% and 51% per month) versus defective (2% and 35% per month) viral genomes. However, intact genomes were still observed one year post chronic treatment initiation in contrast to early treatment where intact genomes were no longer detectable. Moreover, early ART reduced phylogenetic diversity of intact genomes and limited the seeding and persistence of cytotoxic T lymphocyte immune escape variants in the reservoir. Conclusions: Overall, our results show that whereas ART initiated in hyperacute HIV-1 subtype C infection did not impact reservoir seeding, it was nevertheless associated with more rapid decay of intact viral genomes, decreased genetic complexity and immune escape in reservoirs, which could accelerate reservoir clearance when combined with other interventional strategies.

Incorporating Intracellular Processes in Virus Dynamics Models.

In-host models have been essential for understanding the dynamics of virus infection inside an infected individual. When used together with biological data, they provide insight into viral life cycle, intracellular and cellular virus-host interactions, and the role, efficacy, and mode of action of therapeutics. In this review, we present the standard model of virus dynamics and highlight situations where added model complexity accounting for intracellular processes is needed. We present several examples from acute and chronic viral infections where such inclusion in explicit and implicit manner has led to improvement in parameter estimates, unification of conclusions, guidance for targeted therapeutics, and crossover among model systems. We also discuss trade-offs between model realism and predictive power and highlight the need of increased data collection at finer scale of resolution to better validate complex models.

Revisiting the observability and identifiability properties of a popular HIV model.

This paper revisits the observability and identifiability properties of a popular ODE model commonly adopted to characterize the HIV dynamics in HIV-infected patients with antiretroviral treatment. These properties are determined by using the general analytical solution of the unknown input observability problem, introduced very recently in Martinelli (2022). This solution provides the systematic procedures able to determine the state observability and the parameter identifiability of any ODE model, in particular, even in the presence of time varying parameters. Four variants of the HIV model are investigated. They differ because some of their parameters are considered constant or time varying. Fundamental new properties, which also highlight an error in the scientific literature, are automatically determined and discussed. Additionally, for each variant, the paper provides a quantitative answer to the following practical question: What is the minimal external information (external to the available measurements of the system outputs) required to make observable the state and identifiable all the model parameters? The answer to this fundamental question is obtained by exploiting the concept of continuous symmetry, recently introduced in Martinelli (2019). This concept allows us to determine a first preliminary general result which is then applied to the HIV model. Finally, for each variant, the paper concludes by providing a redefinition of the state and of the parameters in order to obtain a full description of the system only in terms of a state which is observable and a set of parameters which are identifiable (both constant and time varying).

Efficient Estimates of Surface Diffusion Parameters for Spatio-Temporally Resolved Virus Replication Dynamics.

Advanced methods of treatment are needed to fight the threats of virus-transmitted diseases and pandemics. Often, they are based on an improved biophysical understanding of virus replication strategies and processes in their host cells. For instance, an essential component of the replication of the hepatitis C virus (HCV) proceeds under the influence of nonstructural HCV proteins (NSPs) that are anchored to the endoplasmatic reticulum (ER), such as the NS5A protein. The diffusion of NSPs has been studied by in vitro fluorescence recovery after photobleaching (FRAP) experiments. The diffusive evolution of the concentration field of NSPs on the ER can be described by means of surface partial differential equations (sufPDEs). Previous work estimated the diffusion coefficient of the NS5A protein by minimizing the discrepancy between an extended set of sufPDE simulations and experimental FRAP time-series data. Here, we provide a scaling analysis of the sufPDEs that describe the diffusive evolution of the concentration field of NSPs on the ER. This analysis provides an estimate of the diffusion coefficient that is based only on the ratio of the membrane surface area in the FRAP region to its contour length. The quality of this estimate is explored by a comparison to numerical solutions of the sufPDE for a flat geometry and for ten different 3D embedded 2D ER grids that are derived from fluorescence z-stack data of the ER. Finally, we apply the new data analysis to the experimental FRAP time-series data analyzed in our previous paper, and we discuss the opportunities of the new approach.

In silico identification of viral loads in cough-generated droplets - Seamless integrated analysis of CFPD-HCD-EWF.

BACKGROUND AND OBJECTIVE: Respiratory diseases caused by respiratory viruses have significantly threatened public health worldwide. This study presents a comprehensive approach to predict viral dynamics and the generation of stripped droplets within the mucus layer of the respiratory tract during coughing using a larynx-trachea-bifurcation (LTB) model. METHODS: This study integrates computational fluid-particle dynamics (CFPD), host-cell dynamics (HCD), and the Eulerian wall film (EWF) model to propose a potential means for seamless integrated analysis. The verified CFPD-HCD coupling model based on a 3D-shell model was used to characterize the severe acute respiratory syndrome, coronavirus 2 (SARS-CoV-2) dynamics in the LTB mucus layer, whereas the EWF model was employed to account for the interfacial fluid to explore the generation mechanism and trace the origin site of droplets exhaled during a coughing event of an infected host. RESULTS: The results obtained using CFPD delineated the preferential deposition sites for droplets in the laryngeal and tracheal regions. Thus, the analysis of the HCD model showed that the viral load increased rapidly in the laryngeal region during the peak of infection, whereas there was a growth delay in the tracheal region (up to day 8 after infection). After two weeks of infection, the high viral load gradually migrated towards the glottic region. Interestingly, the EWF model demonstrated a high concentration of exhaled droplets originating from the larynx. The coupling technique indicated a concurrent high viral load in the mucus layer and site of origin of the exhaled droplets. CONCLUSIONS: This interdisciplinary research underscores the seamless analysis from initial exposure to virus-laden droplets, the dynamics of viral infection in the LTB mucus layer, and the re-emission from the coughing activities of an infected host. Our efforts aimed to address the complex challenges at the intersection of viral dynamics and respiratory health, which can contribute to a more detailed understanding and targeted prevention of respiratory diseases.

SARS-CoV-2 viral dynamics in a placebo-controlled phase 2 study of patients infected with the SARS-CoV-2 Omicron variant and treated with pomotrelvir.

Current guidelines recommend that individuals with moderate COVID-19 disease isolate for 5 days after the first appearance of symptoms or a positive SARS-CoV-2 test. It would be useful to understand the time course of infectious virus production and its correlation with virus detection using a rapid antigen test (RAT) or quantitative reverse transcriptase (qRT)-PCR. In a phase 2 study, 242 vaccinated patients with COVID-19 and at low risk for progression to severe disease initiated 5 days of treatment with pomotrelvir (PBI-0451, a SARS-CoV-2 main protease inhibitor) or placebo within 5 days after symptom onset. The primary endpoint, the proportion of subjects with SARS-CoV-2 viral titers below the limit of detection on Day 3 of treatment in the pomotrelvir versus placebo groups, was not met. No between-group differences in SARS-CoV-2 clearance or symptom resolution or alleviation were observed. Additional analyses evaluated the dynamics of SARS-CoV-2 replication in mid-turbinate nasal swabs and saliva samples using infectious virus assay (IVA), RAT, and qRT-PCR. SARS-CoV-2 cleared rapidly, with negative results first determined by IVA (TCID50 below the limit of detection), followed by the RAT (negative for SARS-CoV-2 N antigen), and qRT-PCR (RNA below the limit of detection), which suggests that delayed initiation of treatment (up to 5 days after symptom onset) may have contributed to the lack of treatment response. Symptom resolution lagged behind viral clearance assessed by IVA and RAT. These data support reliance on a negative RAT to determine when an individual is no longer producing infectious virus and may end isolation.IMPORTANCEA phase 2 double-blind, placebo-controlled study was performed evaluating pomotrelvir, a SARS-CoV-2 Mpro inhibitor, compared with placebo in 242 non-hospitalized, vaccinated, symptomatic adults with COVID-19 (Omicron). No improvement in the decrease of viral replication or relief of symptoms was observed between the two groups when treatment was initiated ≥3 days after symptom onset. These results suggest that future COVID-19 antiviral studies using a similar patient population may need to initiate treatment earlier, like influenza studies. This is the first study to prospectively evaluate SARS-CoV-2 viral dynamics and the time to viral clearance in a significant number of patients using concurrently obtained results from an infectious virus assay, a rapid antigen test (RAT), and a qRT-PCR assay over a 15-day time course. These results suggest that a negative RAT assay is a good indicator of loss of infectious virus and the ability to return to normal activities.